April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
In vivo retinal blood flow cytometry and velocimetry
Author Affiliations & Notes
  • Jesse B Schallek
    Ctr for Visual Science, University of Rochester, Rochester, NY
  • Keith Parkins
    Ctr for Visual Science, University of Rochester, Rochester, NY
  • David R Williams
    Ctr for Visual Science, University of Rochester, Rochester, NY
    Flaum Eye Institute, University of Rochester, Rochester, NY
  • Footnotes
    Commercial Relationships Jesse Schallek, Canon Inc. (F), University of Rochester (P); Keith Parkins, Canon Inc. (F); David Williams, Canon Inc. (F), Pfizer (C), Pfizer (R), Polgenix Inc. (F), University of Rochester (P)
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Investigative Ophthalmology & Visual Science April 2014, Vol.55, 4325. doi:
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      Jesse B Schallek, Keith Parkins, David R Williams; In vivo retinal blood flow cytometry and velocimetry. Invest. Ophthalmol. Vis. Sci. 2014;55(13):4325.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose
 

Blood flow cytometry traditionally requires a blood draw followed by a time consuming process that requires skilled human guidance. Many benefits could be realized if this analysis could be performed noninvasively. Here we show a proof-of-concept in vivo flow cytometer that uses an adaptive optics scanning light ophthalmoscope (AOSLO) to image, classify, count, and report the velocity of thousands of blood cells in the living retina within seconds.

 
Methods
 

Anesthetized mice were imaged with a two-channel AOSLO. One channel imaged capillaries in near infrared reflectance (NIR, 796 nm), a second imaged sodium fluorescein injected systemically (488-514 nm ex, 534/25 nm em). The centroid of each cell in NIR was used to register the fluorescence channel, which helps to distinguish cells from the gaps between them because fluorescein preferentially labels plasma. After AO correction, the slow scanner was stopped, allowing high speed line scans (30,000/second) perpendicular to a retinal vessel (Zhong et al. 2008). Blood cells create a 2-dimensional spatiotemporal image as they move past the 1-dimensional scan (fig 1). The width of the cell can be measured from the line scan dimension. Cell velocity is determined by the cell dwell time in consecutive line scans.

 
Results
 

Cytometry: Based on cell shape, size, scatter and frequency of occurrence, AOSLO cytometry can distinguish multiple cell populations while imaging hundreds to thousands of cells per second. When we focus on the capillary with high confocality, we find that red blood cells have positive contrast in NIR whereas they have negative contrast in fluorescence because cells have less fluorescein than the surrounding plasma (fig 2). Velocimetry: The in vivo cytometer had the capacity to measure cell velocities >100 mm/sec, two orders of magnitude greater than the fastest blood cells in retinal capillaries. This approach enables an absolute measure of blood velocity and variations corresponding to the cardiac diastolic and systolic cycle.

 
Conclusions
 

Retinal flow cytometry provides the first steps toward reducing the need for ex vivo blood analysis. This non-invasive strategy can count, classify, and measure the speed of blood cells in vivo.

     
Keywords: 436 blood supply • 552 imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • 529 flow cytometry  
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